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In this project, an engineer will collaborate with a clinical musculoskeletal specialist to test the characteristics of a photonic sensor with potential applications in a variety of AT.
Physiological validation of a novel photonic biosensor
Start date 1st May 2023
End date 30th September 2023
PI Dr Matthew Dyson (Newcastle University, School of Engineering)
Co-Is Jennifer Olsen (Newcastle University, School of Engineering)
Patrick Degenaar (Newcastle University, School of Engineering)
Annette Pantall (Newcastle University, Faculty of Medical Sciences)
Jacopo Franco (Newcastle University)
We have prototyped a photonic device for sensing muscle activity. Early tests confirm the sensor outputs can track changes associated with muscle activation in various areas of the body. The sensor has attractive properties. Relative to current technology it has componentry that are readily available and very low cost; uses less power and can be adapted to on-demand power usage; is invariant to factors that make electrical biosensors unreliable in warmer climates, and requires less signal conditioning to produce a usable and interpretable output signal.
The sensor has a very small footprint and is low-cost. We anticipate it enabling both low-latency tracking of muscles for control and long-term monitoring of muscles for diagnosis purposes in a range of assistive technology devices. For this to happen, it will first be necessary to validate the precise physiological phenomenon the sensor measurements capture. Clinical affirmation of the manner and the depth to which the sensor can detect changes in muscle position will determine what assistive technology the method is appropriate for and whether the current design should be altered.
In this project, an engineer will collaborate with a clinical musculoskeletal specialist to design and run simple experiments to characterise whether the sensor directly tracks muscle movement and position, or a secondary phenomenon which occurs simultaneously to muscle movement.
Experiments will also aim to provide insight into the type and depth of muscle groups the sensor is appropriate for. Data acquired will provide the necessary clinical support to apply for further funding downstream.